Reliability/risk centered cost effective preventive maintenance planning of generating units

2018 ◽  
Vol 35 (9) ◽  
pp. 2052-2079 ◽  
Author(s):  
Umamaheswari E. ◽  
Ganesan S. ◽  
Abirami M. ◽  
Subramanian S.
Keyword(s):  
Preventive Maintenance ◽  
Optimization Technique ◽  
Solution Space ◽  
Fuzzy Decision Making ◽  
Content Type ◽  
Multi Objective ◽  
Statistical Measures ◽  
Highly Nonlinear ◽  
Optimal Maintenance ◽  
Maintenance Schedules

Purpose Finding the optimal maintenance schedules is the primitive aim of preventive maintenance scheduling (PMS) problem dealing with the objectives of reliability, risk and cost. Most of the earlier works in the literature have focused on PMS with the objectives of leveling reserves/risk/cost independently. Nevertheless, very few publications in the current literature tackle the multi-objective PMS model with simultaneous optimization of reliability, and economic perspectives. Since, the PMS problem is highly nonlinear and complex in nature, an appropriate optimization technique is necessary to solve the problem in hand. The paper aims to discuss these issues. Design/methodology/approach The complexity of the PMS problem in power systems necessitates a simple and robust optimization tool. This paper employs the modern meta-heuristic algorithm, namely, Ant Lion Optimizer (ALO) to obtain the optimal maintenance schedules for the PMS problem. In order to extract best compromise solution in the multi-objective solution space (reliability, risk and cost), a fuzzy decision-making mechanism is incorporated with ALO (FDMALO) for solving PMS. Findings As a first attempt, the best feasible maintenance schedules are obtained for PMS problem using FDMALO in the multi-objective solution space. The statistical measures are computed for the test systems which are compared with various meta-heuristic algorithms. The applicability of the algorithm for PMS problem is validated through statistical t-test. The statistical comparison and the t-test results reveal the superiority of ALO in achieving improved solution quality. The numerical and statistical results are encouraging and indicate the viability of the proposed ALO technique. Originality/value As a maiden attempt, FDMALO is used to solve the multi-objective PMS problem. This paper fills the gap in the literature by solving the PMS problem in the multi-objective framework, with the improved quality of the statistical indices.

Parametric optimization in modified air abrasive jet machining

2019 ◽  
Vol 15 (3) ◽  
pp. 617-629
Author(s):  
S. Rajendra Prasad ◽  
K. Ravindranath K. Ravindranath ◽  
M.L.S. Devakumar M.L.S. Devakumar
Keyword(s):  
Optimization Technique ◽  
Mesh Size ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Abrasive Jet Machining ◽  
Alloy Material ◽  
Size Measure ◽  
First Time

Purpose The choice of best machining parameters is an extremely basic factor in handling of any machined parts. The purpose of this paper is to exhibit a multi-objective optimization technique; in view of weighted aggregate sum product assessment (WASPAS) technique toward upgrade the machining parameters in modified air abrasive jet machining (MAAJM) process: injecting pressure, stand-off distance (SOD), and abrasive mesh size measure with 100 rpm rotatable worktable on Nickel 233 alloy material. Three conflicting destinations, material removal rate (MRR), surface roughness (SR) and taper angles (Ta), respectively, are considered at the same time. The proposed procedure uses WASPAS, which is the examination of parametric optimization of the abrasive jet machining (AJM) process. The results was used any scopes of reactions in MAAJM process is the ideal setting of parameters are resolved through investigations represented. There is wide utilization of Nickel 233 in aviation enterprises; machining information on producing a hole utilizing MAAJM for the first time is given in this work, which will be helpful different industries. Design/methodology/approach This paper exhibits a multi-objective optimization technique; in view of WASPAS technique toward upgrade the machining parameters in MAAJM process: injecting pressure, SOD, and abrasive mesh size measure with 100 rpm rotatable worktable on Nickel 233 alloy material. Findings As an outcome of using the tool in any ranges of responses in the AJM process, the optimal setting of parameters is determined through experiments illustrated. The machining data of generating a hole using AJM are studied for the first time in this work, which will be useful for aerospace industries, where Nickel 233 is used broadly. Originality/value A new material in unconventional machining process and also a multi-objective optimization technique are adopted.

On preventive maintenance policies: a selection framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Imad Alsyouf ◽  
Sadeque Hamdan ◽  
Mohammad Shamsuzzaman ◽  
Salah Haridy ◽  
Iyad Alawaysheh
Keyword(s):  
Preventive Maintenance ◽  
Fuzzy Ahp ◽  
Critical Component ◽  
Multi Objective Optimization ◽  
Maintenance Policy ◽  
Coolant Pump ◽  
Content Type ◽  
Multi Objective ◽  
Maintenance Policies ◽  
Preventive Maintenance Policy

PurposeThis paper develops a framework for selecting the most efficient and effective preventive maintenance policy using multiple-criteria decision making and multi-objective optimization.Design/methodology/approachThe critical component is identified with a list of maintenance policies, and then its failure data are collected and the optimization objective functions are defined. Fuzzy AHP is used to prioritize each objective based on the experts' questionnaire. Weighted comprehensive criterion method is used to solve the multi-objective models for each policy. Finally, the effectiveness and efficiency are calculated to select the best maintenance policy.FindingsFor a fleet of buses in hot climate environment where coolant pump is identified as the most critical component, it was found that block-GAN policy is the most efficient and effective one with a 10.24% of cost saving and 0.34 expected number of failures per cycle compared to age policy and block-BAO policy.Research limitations/implicationsOnly three maintenance policies are compared and studied. Other maintenance policies can also be considered in future.Practical implicationsThe proposed methodology is implemented in UAE for selecting a maintenance scheme for a critical component in a fleet of buses. It can be validated later in other Gulf countries.Originality/valueThis research lays a solid foundation for selecting the most efficient and effective preventive maintenance policy for different applications and sectors using MCDM and multi-objective optimization to improve reliability and avoid economic loss.

Multi-objective optimization of composite two-stage vibration isolation system for sensitive equipment

2016 ◽  
Vol 14 (2) ◽  
pp. 343-361
Author(s):  
Wei Huang ◽  
Jian Xu ◽  
Dayong Zhu ◽  
Cheng Liu ◽  
Jianwei Lu ◽  
...  
Keyword(s):  
Thin Plate ◽  
Vibration Isolation ◽  
Composite System ◽  
Optimization Technique ◽  
Two Stage ◽  
Isolation System ◽  
Vibration Isolation System ◽  
Content Type ◽  
Multi Objective ◽  
Precision Equipment

Purpose The purpose of this paper is to propose a novel strategy of optimal parameters configuration and placement for sensitive equipment. Design/methodology/approach In this study, clamped thin plate is considered as the foundation form, and a novel composite system is proposed based on the two-stage isolation system. By means of the theory of mechanical four-pole connection, the displacement amplitude transmissibility from the thin plate to precision equipment is derived. For the purpose of performing optimal design of the composite system, a novel multi-objective idea is presented. Multi-objective particle swarm optimization (MOPSO) algorithm is adopted as an optimization technique, which can achieve a global optimal solution (gbest), and selecting the desired solution from an equivalent Pareto set can be avoided. Maximum and variance of the four transmitted peak displacements are considered as the fitness functions simultaneously; the purpose is aimed at reducing the amplitude of the multi-peak isolation system, meanwhile pursuing a uniform vibration as far as possible. The optimization is mainly organized as a combination of parameter configuration and placement design, and the traversal search of discrete plate is performed in each iteration for the purpose of achieving the global optimum. Findings An important transmissibility based on the mechanical four-pole connection is derived, and a composite vibration isolation system is proposed, and a novel optimization problem is also defined here. This study reports a novel optimization strategy combined with artificial intelligence for parameters and placement design of precision equipment, which can promote the traditional view of two-stage vibration isolation. Originality/value Two-stage vibration isolation systems are widely applied to the vibration attenuation of precision equipment, but in these traditional designs, vibration participation of foundation is often ignored. In this paper, participation of foundation of equipment is considered, and a coherent new strategy for equipment isolation and foundation vibration is presented. This study shows a new vision of interdisciplinary including civil engineering, mechanical dynamics and computational science.

scholarly journals Optimal Maintenance Thresholds to Perform Preventive Actions by Using Multi-Objective Evolutionary Algorithms

2019 ◽  
Vol 9 (15) ◽  
pp. 3068 ◽  
Author(s):  
Aitor Goti ◽  
Aitor Oyarbide-Zubillaga ◽  
Elisabete Alberdi ◽  
Ana Sanchez ◽  
Pablo Garcia-Bringas
Keyword(s):  
Preventive Maintenance ◽  
Manufacturing Industry ◽  
Industrial Revolution ◽  
Preventive Intervention ◽  
Cost Benefit ◽  
Economic Consequences ◽  
Maintenance Cost ◽  
Optimization Approach ◽  
Multi Objective ◽  
Optimal Maintenance

Maintenance has always been a key activity in the manufacturing industry because of its economic consequences. Nowadays, its importance is increasing thanks to the “Industry 4.0” or “fourth industrial revolution”. There are more and more complex systems to maintain, and maintenance management must gain efficiency and effectiveness in order to keep all these devices in proper conditions. Within maintenance, Condition-Based Maintenance (CBM) programs can provide significant advantages, even though often these programs are complex to manage and understand. For this reason, several research papers propose approaches that are as simple as possible and can be understood by users and modified by experts. In this context, this paper focuses on CBM optimization in an industrial environment, with the objective of determining the optimal values of preventive intervention limits for equipment under corrective and preventive maintenance cost criteria. In this work, a cost-benefit mathematical model is developed. It considers the evolution in quality and production speed, along with condition based, corrective and preventive maintenance. The cost-benefit optimization is performed using a Multi-Objective Evolutionary Algorithm. Both the model and the optimization approach are applied to an industrial case.

Adaptive and noncyclic preventive maintenance to augment production activities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sunil Dutta ◽  
Narala Suresh Kumar Reddy
Keyword(s):  
Preventive Maintenance ◽  
Production Scheduling ◽  
Content Type ◽  
Staff Members ◽  
Novel Approach ◽  
The Hours ◽  
Maintenance Activities ◽  
The Moment ◽  
Maintenance Schedules ◽  
Maintenance Model

PurposeProduction schedules, if not met as per timelines may result in heavy losses to a company in terms of its standing and the overall profit. Production scheduling is generally planned by not taking preventive maintenance schedules into consideration. Most of the plants allocate discrete hours/time for preventive maintenance activities. These hours allocated for preventive maintenance will be in addition to the hours which would be lost during breakdown maintenance. These lost hours may be reduced if production scheduling and preventive maintenance activities are integrated. This advocates that we need to devise a methodology which can take care of lost hours.Design/methodology/approachAdaptive and noncyclic maintenance strategy describes the modification of existing maintenance practices, policies and procedures to meet new dynamic tasks/opportunities. It demands a high degree of flexibility and mental agility from maintenance staff members. The maintenance team has to be on a lookout for an opportunity message received from the central server and has to act promptly. The moment an opportunity arises, a message is forwarded to a central maintenance server (opportunity is captured). The central server then assigns individuals/team, based on their expertise and the maintenance task due on that machine/equipment. This action is completely automated and implemented without delay.FindingsThe total man-hours saved by executing adaptive and noncyclic preventive maintenance methodology comes to 705 h during 15 days on 30 machines installed in three different sections. There was a contribution of 71 innovative ideas from the repair teams. Out of these 71 innovative ideas, 16 were found suitable for execution. A quantum jump in the morale and motivation of the maintenance team was noticed from the feedback forms. Mutual understanding and respect for each other among employees has been enhanced. The optimization of resources and infrastructure including tools, gauges, testing equipment, etc. could truly be attained.Practical implicationsThe developed adaptive and noncyclic preventive maintenance model assists in capturing lost hours and make the system proactive and lean. The suggested model optimizes the preventive and predictive maintenance activities and results in substantial saving of efforts, manpower, resources and allocated budget.Originality/valueThe adaptive and noncyclic preventive maintenance model discussed in the article is a novel approach for the optimization of resources. The technique assists in capturing lost hours and utilization of these hours for preventive maintenance tasks. The model will also encourage creative and innovative ideas from employees and take the organization toward Continual Maintenance Optimization.

Damage identification using combined acceleration and voltage matching with one-dimensional PZT patch model

2018 ◽  
Vol 14 (1) ◽  
pp. 40-64
Author(s):  
K. Shankar ◽  
N. Jinesh
Keyword(s):  
Structural Parameters ◽  
Optimization Technique ◽  
Crack Identification ◽  
Structural Parameter ◽  
Multiple Cracks ◽  
Content Type ◽  
Patch Model ◽  
One Dimensional ◽  
Multi Objective ◽  
Fixed Beam

Purpose The purpose of this paper is to provide an effective and simple technique for structural parameter identification, particularly to identify multiple cracks in a structure using simultaneous measurement of acceleration responses and voltage signals from PZT patches which is a multidisciplinary approach. A hybrid element constituted of one-dimensional beam element and a PZT sensor is used with reduced material properties which is very convenient for beams and is a novel application for inverse problems. Design/methodology/approach Multi-objective formulation is used whereby structural parameters are identified by minimizing the deviation between the predicted and measured values from the PZT patch and acceleration responses, when subjected to excitation. In the proposed method, a patch is attached to either end of the fixed beam. Using particle swarm optimization algorithm, normalized fitness functions are defined for both voltage and acceleration components with weighted aggregation multi-objective optimization technique. The signals are polluted with 5 percent Gaussian noise to simulate experimental noise. The effects of various weighting factors for the combined objective function are studied. The scheme is also experimentally validated by identification of cracks in a fixed-fixed beam. Findings The numerical and experimental results shows that significant improvement in accuracy of damage detection is achieved by the combined multidisciplinary method, when compared with only voltage or only acceleration-matching method as well as with other methods. Originality/value The proposed multidisciplinary crack identification approach, which is based on one-dimensional PZT patch model as well as conventional acceleration method, is not reported in the literature.

Performance evaluation in CNC turning of AA6063-T6 alloy using WASPAS approach

2018 ◽  
Vol 15 (6) ◽  
pp. 700-709 ◽  
Author(s):  
Priyabrata Sahoo ◽  
Mantra Prasad Satpathy ◽  
Vishnu Kumar Singh ◽  
Asish Bandyopadhyay
Keyword(s):  
Surface Roughness ◽  
Goodness Of Fit ◽  
Optimization Technique ◽  
Cutting Parameters ◽  
Confirmatory Test ◽  
Depth Of Cut ◽  
Tool Vibration ◽  
Content Type ◽  
Cnc Turning ◽  
Multi Objective

PurposeSurface roughness and vibration during machining are inevitable which critically affect the product quality characteristics. This paper aims to suggest the implementation of a multi-objective optimization technique to obtain the favorable parametric conditions which lead to minimum tool vibration and surface roughness of 6063-T6 aluminum alloy in computer numerically controlled (CNC) turning.Design/methodology/approachThe case study has been accomplished according to response surface methodology RSM’s Box–Behnken design (BBD) matrix using Titanium Nitride-coated Tungsten Carbide insert in a dry environment. As the experimental results are quite nonlinear, a second-order regression model has been developed for the responses (surface roughness and tool vibration) in terms of input cutting parameters (spindle speed, feed rate and depth of cut). The goodness of fit of the models has also been verified with analysis of variance (ANOVA) results.FindingsThe significance efficacy of input parameters on surface roughness and tool vibrations has been illustrated through multi-objective overlaid 3D surface plots and contour plots. Finally, parametric optimization has been performed to get the desired response values under the umbrella of weighted aggregate sum product assessment (WASPAS) method and verified confidently with confirmatory test results.Originality/valueThe results of this study reveals that hybrid RSM with WASPAS method can be readily applicable to optimize multi-response problems in the manufacturing field with higher confidence.

An operating environment-based preventive maintenance decision model

2019 ◽  
Vol 26 (4) ◽  
pp. 592-610
Author(s):  
Aiping Jiang ◽  
Qingxia Li ◽  
Jinyi Yan ◽  
Leqing Huang ◽  
Haining Wu
Keyword(s):  
Reliability Analysis ◽  
Preventive Maintenance ◽  
Decision Model ◽  
Maintenance Cost ◽  
Redundant System ◽  
Content Type ◽  
Multiple Components ◽  
Safety And Reliability ◽  
Optimal Maintenance ◽  
The Cost

Purpose The purpose of this paper is to focus on finding the optimal maintenance interval and the minimum maintenance cost for redundant system, considering environment factors. Design/methodology/approach The authors propose a decision model with environment-based preventive maintenance for the repairable redundant system. Referring to the k-out-of-n model and Proportional Hazard Model, the reliability analysis is completed for the redundant system affected by internal and external issues. Meanwhile, the maintenance cost for the redundant system is divided into two categories: the fixed maintenance cost involving whole system replacement at the time of system failure, and the cost to replace failure components when the system still functions. Findings Upon the required reliability analysis, an optimal maintenance interval that minimizes the average maintenance cost per unit time is identified. The simulation results indicate that the optimal maintenance interval with consideration of environmental factors is significantly shorter than that without consideration of these factors, with the maintenance cost increase within 10 percent. Practical implications The redundant systems have widely been used in industries including the aero craft control system and warship power system. The model could be applied in the more real case considering the types of components and the operation environment, and help production managers better maintain machines by increasing the safety and reliability of the redundant model with the more frequent inspection. Originality/value Previous research of redundant system always focuses on internal degradation, while ignoring the reliability analysis for a redundant system with various multiple components under the influence of environment. However, this work could fill the theoretical gap, i.e. simultaneously consider both environmental and internal factors for a redundant system with non-homogeneous components. Meanwhile, the proposed superior model increases the reliability and safety of the k-out-of-n model with reasonable cost. Production managers could benefit a lot from this as well.

Multi objective optimization of ECG process under fuzzy environment

2015 ◽  
Vol 11 (3) ◽  
pp. 350-371 ◽  
Author(s):  
G K Bose
Keyword(s):  
Process Parameters ◽  
Supply Voltage ◽  
Optimization Technique ◽  
Research Work ◽  
Experimental Studies ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Multi Objective ◽  
Machining Parameter

Purpose – In the present research work electrochemical grinding (ECG) process is applied to machine Al2O3/Al interpenetrating phase composite. The purpose of this paper is to present a new approach to optimize the ECG process parameters while machining alumina-aluminum (Al2O3 – Al) interpenetrating phase composites (IPC) used in automotive, aircraft and manufacture of space ships applying Taguchi-based experimental studies and fuzzy multi-criteria decision-making techniques. Design/methodology/approach – The present work identifies the process variables that have significant consequences during ECG of Al2O3/Al IPC. The Taguchi L9 orthogonal array is selected for design of experiments and the analysis is carried out following signal to noise ratio. The analysis of variance is carried out to establish the factors that significantly influence the responses. The present work also investigates the multi objective optimization of ECG process parameters using VIseKriterijumsa Optimizacija I Kompromisno Resenje (VIKOR) and Grey relational analysis (GRA) to establish the reference ranking from a set of alternatives in the presence of conflicting criteria. Findings – Material removal rate, surface finish, overcut and cutting force are shown to depend on the type of electrolyte, supply voltage, depth of cut and electrolyte flow rate. It is found that voltage and electrolyte concentration are important. The optimal machining parameter combination for ECG process is determined using fuzzy set theory, VIKOR and GRA. Substantial improvement in machining performance takes place. Practical implications – A variety of manufacturing techniques are available for processing of Al2O3 – Al metal matrix composites. Generally manufacturers favor low cost modus operandi. Therefore ECG process is the best alternative for processing of MMCs in the present commercial sectors. The experimental investigation approach can act as useful and an efficient guideline for manufacturing. Originality/value – The characteristic features of the ECG process are reflected through Taguchi design-based experimental studies with various process parametric combinations. Application of multi-response optimization technique for evaluation of best parametric combination for machining Al2O3 – Al IPC material using ECG process is a first-of-its-kind approach in literature.

scholarly journals Multi-Objective Energy Management and Charging Strategy for Electric Bus Fleets in Cities Using Various ECO Strategies

2021 ◽  
Vol 13 (14) ◽  
pp. 7865
Author(s):  
Mohammed Mahedi Hasan ◽  
Nikos Avramis ◽  
Mikaela Ranta ◽  
Andoni Saez-de-Ibarra ◽  
Mohamed El Baghdadi ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Thermal Management ◽  
Energy Management ◽  
Management Strategy ◽  
Energy Requirement ◽  
Optimization Technique ◽  
Total Cost ◽  
Multi Objective ◽  
Battery Capacity ◽  
Eco Features

The paper presents use case simulations of fleets of electric buses in two cities in Europe, one with a warm Mediterranean climate and the other with a Northern European (cool temperate) climate, to compare the different climatic effects of the thermal management strategy and charging management strategy. Two bus routes are selected in each city, and the effects of their speed, elevation, and passenger profiles on the energy and thermal management strategy of vehicles are evaluated. A multi-objective optimization technique, the improved Simple Optimization technique, and a “brute-force” Monte Carlo technique were employed to determine the optimal number of chargers and charging power to minimize the total cost of operation of the fleet and the impact on the grid, while ensuring that all the buses in the fleet are able to realize their trips throughout the day and keeping the battery SoC within the constraints designated by the manufacturer. A mix of four different types of buses with different battery capacities and electric motor specifications constitute the bus fleet, and the effects that they have on charging priority are evaluated. Finally, different energy management strategies, including economy (ECO) features, such as ECO-comfort, ECO-driving, and ECO-charging, and their effects on the overall optimization are investigated. The single bus results indicate that 12 m buses have a significant battery capacity, allowing for multiple trips within their designated routes, while 18 m buses only have the battery capacity to allow for one or two trips. The fleet results for Barcelona city indicate an energy requirement of 4.42 GWh per year for a fleet of 36 buses, while for Gothenburg, the energy requirement is 5 GWh per year for a fleet of 20 buses. The higher energy requirement in Gothenburg can be attributed to the higher average velocities of the bus routes in Gothenburg, compared to those of the bus routes in Barcelona city. However, applying ECO-features can reduce the energy consumption by 15% in Barcelona city and by 40% in Gothenburg. The significant reduction in Gothenburg is due to the more effective application of the ECO-driving and ECO-charging strategies. The application of ECO-charging also reduces the average grid load by more than 10%, while shifting the charging towards non-peak hours. Finally, the optimization process results in a reduction of the total fleet energy consumption of up to 30% in Barcelona city, while in Gothenburg, the total cost of ownership of the fleet is reduced by 9%.

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